基于大数据的输电线路阻抗参数预测方法

为解决输电线路阻抗参数测量不准确等问题,提出了基于大数据的输电线路阻抗参数量测方法.对传统未换位导线的参数模型进行了分析,说明了 π 型等值网络中物理量的关系.分析了输电线路参数预测物理量以及估计的模型.对三相线路的潮流计算模型进行了分析,说明了以 SCADA 为量测系统的大数据输电线路参数预测方法.并针对负荷波动提出了准稳态状态估计方法.最后利用仿真模型进行了仿真分析,说明了所提方法的有效性.

Big Data-based Method for Predicting Transmission Line Impedance Parameters

In order to solve the problems of inaccurate measurement of transmission line impedance parameters , a measurement method of transmission line impedance parameters based on big data is proposed．The parameter model of the traditional untransposed wire is analyzed , and the relationship of the physical quantities in the π-type equivalent network is explained．The predicted physical quantities of transmission line parameters and the estimated model are analyzed．The power flow calculation model of the three-phase line is analyzed , and the big data transmission line parameter prediction method using SCADA as the measurement system is explained．A quasi-steady state estimation method is proposed for load fluctuations．Finally , a simulation analysis is carried out using a simulation model, which demonstrates the effectiveness of the method proposed in this paper．